摘要：Apartments have become a new trend in the market over the past few years. This type of real estate is becoming more and more popular every year, both among investors and tourists. The purpose of the article is to make a forecast of prices for apartments in St. Petersburg. Research methods: description, comparison, analogy, generalization and analysis. In the course of the study, the dynamics of changes in prices per square meter of apartments in St. Petersburg for 2014-2019 is considered; the main factors influencing the price index of apartments in St. Petersburg are identified. The influence of the identified factors on the price indicator is analysed on the basis of multiple linear regression. The study showed that almost all factors have a fairly strong relationship with the resulting indicator. The most significant factors are identified, on the basis of which the final model of the cost of apartments is built. On the basis of the exponential smoothing method, an assessment of changes in factors in the forecast period was made and a forecast of apartment prices was made based on the obtained values. The study shows that apartment prices will rise in the coming period. The forecast of the cost of service apartments developed by the authors can have a positive effect when conducting real estate transactions in St. Petersburg.
其他摘要：Apartments have become a new trend in the market over the past few years. This type of real estate is becoming more and more popular every year, both among investors and tourists. The purpose of the article is to make a forecast of prices for apartments in St. Petersburg. Research methods: description, comparison, analogy, generalization and analysis. In the course of the study, the dynamics of changes in prices per square meter of apartments in St. Petersburg for 2014-2019 is considered; the main factors influencing the price index of apartments in St. Petersburg are identified. The influence of the identified factors on the price indicator is analysed on the basis of multiple linear regression. The study showed that almost all factors have a fairly strong relationship with the resulting indicator. The most significant factors are identified, on the basis of which the final model of the cost of apartments is built. On the basis of the exponential smoothing method, an assessment of changes in factors in the forecast period was made and a forecast of apartment prices was made based on the obtained values. The study shows that apartment prices will rise in the coming period. The forecast of the cost of service apartments developed by the authors can have a positive effect when conducting real estate transactions in St. Petersburg.
